1. Field of the Invention
The present invention relates generally to the generation of chemical entities with defined physical, chemical or bioactive properties, and particularly to the automatic generation of drug leads via computer-based, iterative robotic synthesis and analysis of directed diversity chemical libraries.
2. Related Art
Conventionally, new chemical entities with useful properties are generated by identifying a chemical compound (called a xe2x80x9clead compoundxe2x80x9d) with some desirable property or activity, creating variants of the lead compound, and evaluating the property and activity of those variant compounds. Examples of chemical entities with useful properties include paints, finishes, plasticizers, surfactants, scents, flavorings, and bioactive compounds, but can also include chemical compounds with any other useful property that depends upon chemical structure, composition, or physical state. Chemical entities with desirable biological activities include drugs, herbicides, pesticides, veterinary products, etc. There are a number of flaws with this conventional approach to lead generation, particularly as it pertains to the discovery of bioactive compounds.
One deficiency pertains to the first step of the conventional approach, i.e., the identification of lead compounds. Traditionally, the search for lead compounds has been limited to an analysis of compound banks, for example, available commercial, custom, or natural products chemical libraries. Consequently, a fundamental limitation of the conventional approach is the dependence upon the availability, size, and structural diversity of these chemical libraries. Although chemical libraries cumulatively total an estimated 9 million identified compounds, they reflect only a small sampling of all possible organic compounds with molecular weights less than 1200. Moreover, only a small subset of these libraries is usually accessible for biological testing. Thus, the conventional approach is limited by the relatively small pool of previously identified chemical compounds which may be screened to identify new lead compounds.
Also, compounds in a chemical library are traditionally screened (for the purpose of identifying new lead compounds) using a combination of empirical science and chemical intuition. However, as stated by Rudy M. Baum in his article xe2x80x9cCombinatorial Approaches Provide Fresh Leads for Medicinal Chemistry,xe2x80x9d CandEN, Feb. 7, 1994, pages 20-26, xe2x80x9cchemical intuition, at least to date, has not proven to be a particularly good source of lead compounds for the drug discovery process.xe2x80x9d
Another deficiency pertains to the second step of the conventional approach, i.e., the creation of variants of lead compounds. Traditionally, lead compound variants are generated by chemists using conventional chemical synthesis procedures. Such chemical synthesis procedures are manually performed by chemists. Thus, the generation of lead compound variants is very labor intensive and time consuming. For example, it typically takes many chemist years to produce even a small subset of the compound variants for a single lead compound. Baum, in the article referenced above, states that xe2x80x9cmedicinal chemists, using traditional synthetic techniques, could never synthesize all of the possible analogs of a given, promising lead compoundxe2x80x9d (emphasis added). Thus, the use of conventional, manual procedures for generating lead compound variants operates to impose a limit on the number of compounds that can be evaluated as new drug leads. Overall, the traditional approach to new lead generation is an inefficient, labor-intensive, time consuming process of limited scope.
Recently, attention has focused on the use of combinatorial chemical libraries to assist in the generation of new chemical compound leads. A combinatorial chemical library is a collection of diverse chemical compounds generated by either chemical synthesis or biological synthesis by combining a number of chemical xe2x80x9cbuilding blocksxe2x80x9d such as reagents. For example, a linear combinatorial chemical library such as a polypeptide library is formed by combining a set of chemical building blocks called amino acids in every possible way for a given compound length (i.e., the number of amino acids in a polypeptide compound). Millions of chemical compounds theoretically can be synthesized through such combinatorial mixing of chemical building blocks. For example, one commentator has observed that the systematic, combinatorial mixing of 100 interchangeable chemical building blocks results in the theoretical synthesis of 100 million tetrameric compounds or 10 billion pentameric compounds (Gallop et al., xe2x80x9cApplications of Combinatorial Technologies to Drug Discovery, Background and Peptide Combinatorial Libraries,xe2x80x9d Journal of Medicinal Chemistry, Volume 37, Number 9, pages 1233-1250, Apr. 29, 1994).
To date, most work with combinatorial chemical libraries has been limited only to peptides and oligonucleotides for the purpose of identifying bioactive agents; little research has been performed using non-peptide, non-nucleotide based combinatorial chemical libraries. It has been shown that the compounds in peptide and oligonucleotide based combinatorial chemical libraries can be assayed to identify ones having bioactive properties. However, there is no consensus on how such compounds (identified as having desirable bioactive properties and desirable profile for medicinal use) can be used.
Some commentators speculate that such compounds could be used as orally efficacious drugs. This is unlikely, however, for a number of reasons. First, such compounds would likely lack metabolic stability. Second, such compounds would be very expensive to manufacture, since the chemical building blocks from which they are made most likely constitute high priced reagents. Third, such compounds would tend to have a large molecular weight, such that they would have bioavailability problems (i.e., they could only be taken by injection).
Others believe that the compounds from a combinatorial chemical library that are identified as having desirable biological properties could be used as lead compounds. Variants of these lead compounds could be generated and evaluated in accordance with the conventional procedure for generating new bioactive compound leads, described above. However, the use of combinatorial chemical libraries in this manner does not solve all of the problems associated with the conventional lead generation procedure. Specifically, the problem associated with manually synthesizing variants of the lead compounds is not resolved.
In fact, the use of combinatorial chemical libraries to generate lead compounds exacerbates this problem. Greater and greater diversity has often been achieved in combinatorial chemical libraries by using larger and larger compounds (that is, compounds having a greater number of variable subunits, such as pentameric compounds instead of tetrameric compounds in the case of polypeptides). However, it is more difficult, time consuming, and costly to synthesize variants of larger compounds. Furthermore, the real issues of structural and functional group diversity are still not directly addressed; bioactive agents such as drugs and agricultural products possess diversity that could never be achieved with available peptide and oligonucleotide libraries since the available peptide and oligonucleotide components only possess limited functional group diversity and limited topology imposed through the inherent nature of the available components. Thus, the difficulties associated with synthesizing variants of lead compounds are exacerbated by using typical peptide and oligonucleotide combinatorial chemical libraries to produce such lead compounds. The issues described above are not limited to bioactive agents but rather to any lead generating paradigm for which a chemical agent of defined and specific activity is desired.
Thus, the need remains for a system and method for efficiently and effectively generating new leads designed for specific utilities.
The present invention is directed to a computer based system and method for automatically generating chemical entities with desired physical, chemical and/or biological properties. The present invention is also directed to the chemical entities produced by this system and method. For purposes of illustration, the present invention is described herein with respect to the production of drug leads. However, the present invention is not limited to this embodiment.
Specifically, the present invention is directed to an iterative process for generating new chemical compounds with a prescribed set of physical, chemical and/or biological properties, and to a system for implementing this process. During each iteration of the process, (1) a directed diversity chemical library is robotically generated in accordance with robotic synthesis instructions; (2) the compounds in the directed diversity chemical library are analyzed under computer control, and structure activity/structure-property models (collectively referred to as structure-activity models hereafter) are constructed and/or refined; and (3) new robotic synthesis instructions are generated to control the synthesis of the directed diversity chemical library for the next iteration.
More particularly, during each iteration of the process, the system of the present invention robotically synthesizes, in accordance with robotic synthesis instructions, a directed diversity chemical library comprising a plurality of chemical compounds. The chemical compounds are robotically analyzed to obtain structure-activity/structure-property data (collectively referred to as structure-activity data hereafter) pertaining thereto. The structure-activity data is stored in a structure-activity/structure-property database (referred to as structure-activity database hereafter). The structure-activity database also stores therein structure-activity data pertaining to previously synthesized compounds.
The system of the present invention evaluates, under computer control, the structure-activity data of the chemical compounds obtained from all previous iterations (or a subset of all previous iterations as specified by user input, for example) and constructs structure-activity models that substantially conform to the observed data.
The system of the present invention then identifies, under computer control, reagents, from a reagent database, which, when combined, will produce compounds which are predicted to (1) exhibit improved activity/properties, (2) test the validity of the current structure-activity models, and/or (3) discriminate between the various structure-activity models. Under the system of the present invention, a plurality of structure-activity models may be tested and evaluated in parallel.
Then, the system of the present invention generates, under computer control, new robotic synthesis instructions which, when executed, enable robotic synthesis of chemical compounds from selected combinations of the identified reagents. Such new robotic synthesis instructions are used to generate a new directed diversity chemical library during the next iteration.
Further features and advantages of the present invention, as well as the structure and operation of various embodiments of the present invention, are described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers indicate identical or functionally similar elements. Also, the left most digit(s) of the reference numbers identify the drawings in which the associated elements are first introduced.